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Contains fulltext : 271043.pdf (Publisher’s version ) (Open Access) In the January 2022 issue of Perspectives, Götz et al. argued that small effects are "the indispensable foundation for a cumulative psychological science." They supported their argument by claiming that (a) psychology, like genetics, consists of complex phenomena explained by additive small effects; (b) psychological-research culture rewards large effects, which means small effects are being ignored; and (c) small effects become meaningful at scale and over time. We rebut these claims with three objections: First, the analogy between genetics and psychology is misleading; second, p values are the main currency for publication in psychology, meaning that any biases in the literature are (currently) caused by pressure to publish statistically significant results and not large effects; and third, claims regarding small effects as important and consequential must be supported by empirical evidence or, at least, a falsifiable line of reasoning. If accepted uncritically, we believe the arguments of Götz et al. could be used as a blanket justification for the importance of any and all "small" effects, thereby undermining best practices in effect-size interpretation. We end with guidance on evaluating effect sizes in relative, not absolute, terms. 5 p.

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.

Behavioral science is overly focused on a small subset of the global population. This leads to a “generalizability problem” because the degree to which behavioral science theories adequately capture the psychology of populations outside this small subset is unknown. “Big team science” projects, which involve huge teams of collaborators from research labs all over the world that run participants using a common protocol1, have been heralded as a solution to this “generalizability problem” because they provide a way for researchers to recruit participants from many regions rather than just one. Here we evaluate the adequacy of one such big team science project which claimed the “globalizability” of temporal discounting, the phenomenon in which the subjective value of deferred rewards is smaller than immediate rewards2. Although the project recruited 171 researchers from 109 institutions, and 13629 research participants speaking 40 languages across 61 countries, we argue that relying solely on the typical big team methodology created an "illusion of generalizability", leading authors to overestimate the extent to which research findings can be applied globally. We found that, across low-, middle-, and high-income countries, samples were all similarly young, well-educated, urban, digitally-connected, and the authors were largely concentrated in the Global North. This homogeneity belies the heterogeneity present within each country3,4. We argue that researchers using big team science methods should more closely attend to how their methods include or exclude underrepresented populations, thereby avoiding the “illusion of generalizability”.

The trend for large-scale collaboration has the potential to improve researcher, cultural, and participant diversity. Conducting in-person research requires the examination of challenges and payoffs of competing priorities in what constitutes 'good' research. We describe these challenges and potential resolutions and payoffs in advancing big-team science.

Discrimination on the basis of caste, a descent-based identity marked by handed-down ways of life and custom-based social rules, burdens the daily life of millions of marginalized citizens in South Asia and its diaspora. Yet, this type of discrimination has received little focus in psychology, possibly because of psychology’s over-focus on US contexts, at the expense of contexts in places like South Asia. In this paper, we examine how psychological frameworks designed to explain intergroup relations have been influenced by the history of race in the United States. Frameworks of intergroup phenomena can benefit from centering a construct that is shaped by a distinct historical context and manifests as a covert characteristic, like caste. Unlike forms of racial bias that are considered to be characterized by inner conflict, bias against disadvantaged caste groups can be both uncensored and overt. We compare and contrast the perception, categorisations, legal restrictions, and the nature of bias of race and caste-based discrimination, and argue that equating caste in South Asia with descent-based identities in North America could hinder efforts to combat intergroup discrimination in other parts of the world, especially when we use the causes of bias to develop effective prejudice-reducing strategies.

Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, these five challenges may share a common cause: insufficient investment of intellectual and nonintellectual resources into the typical psychology study. We suggest that the emerging emphasis on big-team science can help address these challenges by allowing researchers to pool their resources together to increase the amount available for a single study. However, the current incentives, infrastructure, and institutions in academic science have all developed under the assumption that science is conducted by solo principal investigators and their dependent trainees, an assumption that creates barriers to sustainable big-team science. We also anticipate that big-team science carries unique risks, such as the potential for big-team-science organizations to be co-opted by unaccountable leaders, become overly conservative, and make mistakes at a grand scale. Big-team-science organizations must also acquire personnel who are properly compensated and have clear roles. Not doing so raises risks related to mismanagement and a lack of financial sustainability. If researchers can manage its unique barriers and risks, big-team science has the potential to spur great progress in psychology and beyond.

When psychologists attend to Africa, they usually test whether theories and concepts developed in North America and Europe generalize to Africa. Psychology would be enriched by focusing on Africa on its own terms.

Social norms can frame how typical and appropriate choices available to people are. Despite the important role of both descriptive and injunctive norms for intervention, few measures distinguish these perceptions. Fewer still are developed for settings where behaviorally-informed development interventions are implemented. This study develops the Strength of Social Gender Norms (SSGN) scale with 399 adolescents aged 14-17 years, to address gaps in measuring social norms that govern women’s employment in India. Exploratory factor analysis demonstrated a good two-factor structure. Psychometric analyses satisfied tests for internal consistency, differentiated it from attitudes, and found moderate test-retest reliability. The measure distinguishes different aspects of social norms among low-income Indian adolescents, a population that is neglected in psychology research at large.

Following theories of emotional embodiment, the facial feedback hypothesis suggests that individuals' subjective experiences of emotion are influenced by their facial expressions. However, evidence for this hypothesis has been mixed. We thus formed a global adversarial collaboration and carried out a preregistered, multicentre study designed to specify and test the conditions that should most reliably produce facial feedback effects. Data from n = 3,878 participants spanning 19 countries indicated that a facial mimicry and voluntary facial action task could both amplify and initiate feelings of happiness. However, evidence of facial feedback effects was less conclusive when facial feedback was manipulated unobtrusively via a pen-in-mouth task., National Science Centre, Poland [2019/35/B/HS6/00528]; JSPS KAKENHI [16H03079, 17H00875, 18K12015, 20H04581, 21H03784]; National Council for Scientific and Technological Development (CNPq); Polish National Science Center; DFG Beethoven grant [2016/23/G/HS6/01775]; National Science Foundation Graduate Research Fellowship [R010138018]; Ministerio de Ciencia, Innovacion y Universidades [PGC2018-098558-B-I00]; Comunidad de Madrid [H2019/HUM-5705]; Teesside University; Occidental College Academic Student Project Award, This work was financially supported by B. Stastny, who generously donated funds for this research in memory of his father, Bill Stastny (J.T.L.). The work was also supported by the National Science Centre, Poland (grant no. 2019/35/B/HS6/00528; K.B.), JSPS KAKENHI (grant nos 16H03079, 17H00875, 18K12015, 20H04581 and 21H03784; Y.Y.), the National Council for Scientific and Technological Development (CNPq; R.M.K.F.), the Polish National Science Center (M.P.), the DFG Beethoven grant no. 2016/23/G/HS6/01775 (M.P.), the National Science Foundation Graduate Research Fellowship (grant no. R010138018; N.A.C.), the Ministerio de Ciencia, Innovacion y Universidades (grant no. PGC2018-098558-B-I00; J.A.H.), the Comunidad de Madrid (grant no. H2019/HUM-5705; J.A.H.), Teesside University (N.B.) and the Occidental College Academic Student Project Award (S.L.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We also thank C. Scavo and A. Bidani for help with translating the study materials, L. Pullano and R. Giorgini for help with coding, and E. Tolomeo and L. Pane for help with data collection.

Correction to: Nature Human Behaviour https://doi.org/10.1038/s41562-021-01173-x, published online 2 August 2021.In the version of this article initially published, the following authors were omitted from the author list and the Author contributionssection for “investigation” and “writing and editing”: Nandor Hajdu (Institute of Psychology, ELTE Eötvös Loránd University, Budapest,Hungary), Jordane Boudesseul (Facultad de Psicología, Instituto de Investigación Científica, Universidad de Lima, Lima, Perú), RafałMuda (Faculty of Economics, Maria Curie-Sklodowska University, Lublin, Poland) and Sandersan Onie (Black Dog Institute, UNSWSydney, Sydney, Australia & Emotional Health for All Foundation, Jakarta, Indonesia). In addition, Saeideh FatahModares’ name wasoriginally misspelled as Saiedeh FatahModarres in the author list. Further, affiliations have been corrected for Maria Terskova (NationalResearch University Higher School of Economics, Moscow, Russia), Susana Ruiz Fernandez (FOM University of Applied Sciences,Essen; Leibniz-Institut fur Wissensmedien, Tubingen, and LEAD Research Network, Eberhard Karls University, Tubingen, Germany),Hendrik Godbersen (FOM University of Applied Sciences, Essen, Germany), Gulnaz Anjum (Department of Psychology, Simon FraserUniversity, Burnaby, Canada, and Department of Economics & Social Sciences, Institute of Business Administration, Karachi, Pakistan).

We conducted a pre-registered meta-analysis to appraise available evidence on two stress regulation strategies: Self-administered mindfulness meditation and heart rate variability biofeedback. We used a combination of keywords to find as many experimental and observational studies as possible, all of which highlighted a link between the two strategies and different components of stress (physiological, affective, and cognitive) and affective consequences of stress. To provide publication bias-corrected estimates, we employed multilevel regression-based methods and permutation-based selection models. We found no evidence for the efficacy of either strategy, which is mostly due to the low quality of the literature, high heterogeneity, high risk of bias, and the lack of Registered Reports. We recommend against relying on these interventions prior to obtaining a more reliable evidence base.

Improving the generalizability of psychology findings to a culture requires sampling participants in that culture. Yet psychology studies rarely sample from African populations, even though it represents 17% of the overall world population. This study aimed to conduct an African-led replication study to test whether Rottman and Young’s “mere-trace” hypothesis of moral reasoning (that people are more sensitive to the dosage of harm-based transgressions than purity transgressions) extends to several African communities. We used a training method developed by the Collaborative Replication and Education Project (CREP) to support and train 23 African collaborators. During this process, we conducted a paradigmatic replication of Rottman’s and Young’s test of the mere trace hypothesis in Egypt, Malawi, Morocco, Mozambique, Nigeria, South Africa, and Tanzania. [We did not find/We found] evidence for the main interaction effect (bdomain x dose = xxx) of transgression severity on the moral wrongness judgment of impure and harmful violations. [We did/ However, we did not] replicate Rottman and Young's findings among Africans. This project helped improve the research capacity of our participating African sites and will support other researchers in collaborating with African scholars.

Spurred by a crisis in their confidence in past findings, psychology in North America, Europe, and Australia has been undergoing a credibility revolution, which has spurred the development and popularization of open science practices to improve the research process. Alongside this development, a broad array of stakeholders have noted that African science is at its own crossroads, as investments in this sector can facilitate human development on the continent. Here we argue that these two movements can facilitate each other: psychology in North America and Europe can benefit from stronger psychology research communities on the African continent, while African scientists can benefit from credible evidence generated through open, freely-available open science practices and tools. However, this synergy will only materialize if a wide array of stakeholders invest in African science through providing resources, training, and specially adapted research tools while simultaneously avoiding ethical pitfalls such as corruption and research colonialism.

In a now-classic study by Srull and Wyer (1979), people who were exposed to phrases with hostile content subsequently judged a man as being more hostile. And this “hostile priming effect” has had a significant influence on the field of social cognition over the subsequent decades. However, a recent multi-lab collaborative study (McCarthy et al., 2018) that closely followed the methods described by Srull and Wyer (1979) found a hostile priming effect that was nearly zero, which casts doubt on whether these methods reliably produce an effect. To address some limitations with McCarthy et al. (2018), the current multi-site collaborative study included data collected from 29 labs. Each lab conducted a close replication (total N = 2,123) and a conceptual replication (total N = 2,579) of Srull and Wyer's methods. The hostile priming effect for both the close replication (d = 0.09, 95% CI [-0.04, 0.22], z = 1.34, p =.16) and the conceptual replication (d = 0.05, 95% CI [-0.04, 0.15], z = 1.15, p =.58) were not significantly different from zero and, if the true effects are non-zero, were smaller than what most labs could feasibly and routinely detect. Despite our best efforts to produce favorable conditions for the effect to emerge, we did not detect a hostile priming effect. We suggest that researchers should not invest more resources into trying to detect a hostile priming effect using methods like those described in Srull and Wyer (1979)., NA

This document estimates the Psychological Science Accelerator’s study capacity for the 2020-2021 academic year. As described in our Study Capacity Policy, study capacity is determined by the PSA’s data collection capacity, or the amount and kind of participant data the PSA can collect in a given year, and its administrative capacity, or its ability to perform the administrative tasks required to collect participant data. Here are five big-picture takeaways on the PSA’s study capacity for 2020-2021: (1) The PSA currently has 1400+ members from 71 countries; (2) Out of seven studies, six are still underway collecting data; (3) Based on our past data collection capacity, we have the ability to recruit a minimum of 20,000 participants over the upcoming scholarly year for new PSA projects; (4) Two out of three PSA members come from so-called “WEIRD” countries (defined in this report as North America and Western Europe); (5) We do not have sufficient information to accurately estimate the number of administrative hours available for each PSA role.

Social and behavioural scientists have attempted to speak to the COVID-19 crisis. But is behavioural research on COVID-19 suitable for making policy decisions? We offer a taxonomy that lets our science advance in Evidence Readiness Levels to be suitable for policy. We caution practitioners to take extreme care translating our findings to applications.

Among animals, natural selection has resulted in a broad array of behavioural strategies to maintain core body temperature in a relatively narrow range. One important temperature regulation strategy is social thermoregulation , which is often done by warming the body together with conspecifics. The literature suggests that the same selection pressures that apply to other animals also apply to humans, producing individual differences in the tendency to socially thermoregulate. We wanted to investigate whether differences in social thermoregulation desires extend to other personality factors in a sample of French students. We conducted an exploratory, hypothesis-generating cross-sectional project to examine associations between thermoregulation and personality. We used conditional random forests in a training segment of our dataset to identify clusters of variables most likely to be shaped by individual differences to thermoregulate. We used the resulting clusters to fit hypothesis-generating mediation models. After we replicated the relationships in two datasets, personality was not related to social thermoregulation desires, with the exception of attachment avoidance. Attachment avoidance in turn predicted loneliness. This mediation proved robust across all three datasets. As our cross-sectional studies allow limited causal inferences, we suggest investing into prospective studies to understand whether and how social thermoregulation shapes attachment avoidance early in life and loneliness later in life. We also recommend replication of the current relationships in other climates, countries, and age groups.

Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, these five challenges may share a common cause: insufficient investment of intellectual and non-intellectual resources into the typical psychology study. We suggest that the emerging emphasis on big team science can help address these challenges by allowing researchers to pool their resources together to increase the amount available for a single study. However, the current incentives, infrastructure, and institutions in academic science have all developed under the assumption that science is conducted by solo Principal Investigators and their dependent trainees, an assumption that creates barriers to sustainable big team science. We also anticipate that big team science carries unique risks, such as the potential for big team science organizations to be co-opted by unaccountable leaders, become overly conservative, and make mistakes at a grand scale. Big team science organizations must also acquire personnel who are properly compensated and have clear roles, raising risks related to mismanagement and a lack of financial sustainability. If researchers can manage its unique barriers and risks, big team science has the potential to spur great progress in psychology and beyond.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion regulation strategy which modifies how one thinks about a situation. Participants from 87 countries/regions (N = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vs. both control conditions) had consistent effects in reducing negative emotions and increasing positive emotions across different measures. Reconstrual and repurposing had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world to build resilience during the pandemic and beyond.

The Psychological Science Accelerators Rapid-Response COVID-19 Project (PSACR) is a project to rapidly select and conduct rigorous, multi-site, and multinational research to understand the psychological and behavioral aspects of the COVID-19 crisis. Here we describe the process we used to select our projects and our general methods for implementing them. We will update this document periodically throughout the projects lifecycle.

According to stereotype threat theory, the possibility of confirming a negative group stereotype evokes feelings of threat, leading people to underperform in domains where they are stereotyped as lacking ability. This theory has immense theoretical and practical implications. However, many studies supporting it include small samples and varying operational definitions of “stereotype threat”. We address the first challenge by leveraging a network of psychology labs to recruit a large Black student sample (Nanticipated = 2700) from multiple US sites (Nanticipated = 27). We address the second challenge by identifying three threat-increasing and three threat-decreasing procedures that could plausibly affect performance and use an adaptive Bayesian design to determine which operationalization yields the strongest evidence for underperformance. This project should advance our knowledge of a scientifically and socially important topic: the conditions under which stereotype threat affects performance among current Black students in the United States.

The National Institutes of Health uses small groups of scientists to judge the quality of the grant proposals that they receive, and these quality judgments form the basis of its funding decisions. In order for this system to fund the best science, the subject experts must, at a minimum, agree as to what counts as a “quality” proposal. We investigated the degree of agreement by leveraging data from a recent experiment with 412 scientist reviewers, each of whom reviewed 3 proposals, and 48 NIH R01 proposals (half funded and half unfunded), each of which was reviewed by between 21 and 30 reviewers. Across all dimensions of NIH’s official rubric, we find low agreement among reviewers in their judgments of scientific merit. For judgments of Overall Impact, which has the greatest weight in funding decisions, we estimate that three reviewers yield a reliability .2, and 12 reviewers would be required to bring this reliability up to .5. Supplemental analyses found that reviewers are even less reliable in the language they use to describe proposals.

Source at https://doi.org/10.1177/2515245918797607. Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions or replicate prior research in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time limited), efficient (in that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.

According to the Justified True Belief account of knowledge (JTB), a person can only truly know something if they have a belief that is both justified and true (i.e., knowledge is justified true belief). This account was challenged by Gettier (1963), who argued that JTB does not explain knowledge attributions in certain situations, later called Gettier-type cases, wherein a protagonist is justified in believing something to be true but their belief was only correct due to luck. Lay people may not attribute knowledge to protagonists with justified but only luckily true beliefs. While some research has found evidence for these so-called Gettier intuitions (e.g., Machery et al., 2017a), Turri et al. (2015) found that participants attributed knowledge in Gettier-type cases at rates similar to cases of justified true belief. In a large-scale, cross-cultural conceptual replication of Turri and colleagues’ (2015) Experiment 1 (N = 4724), we failed to replicate this null result using a within-subjects design and three vignettes across 19 geopolitical regions. Instead, participants demonstrated Gettier intuitions; they were 1.86 times more likely to attribute knowledge to protagonists in standard cases of justified true belief than to protagonists in Gettier-type cases. These results suggest that Gettier intuitions may be common across different scenarios and cultural contexts. When assessing the knowledge of others, lay people may rely on a shared set of epistemic intuitions (i.e., a core folk epistemology) that requires more than simply justification, belief, and truth. However, the size of the Gettier intuition effect did vary by vignette, and the Turri et al. (2015) vignette produced the smallest effect. Thus, epistemic intuitions may also depend on contextual factors unrelated to the criteria of knowledge, such as the characteristics of the protagonist being evaluated.

Many granting agencies allow reviewers to know the identity of a proposal’s Principal Investigator (PI), which opens the possibility that reviewers discriminate on the basis of PI race and gender. We investigated this experimentally with 48 NIH R01 grant proposals, representing a broad spectrum of NIH-funded science. We modified PI names to create separate White male, White female, Black male, and Black female versions of each proposal, and 412 scientists each submitted initial reviews for three proposals. We find little to no race or gender bias in initial R01 evaluations, and additionally find that any bias that might have been present must be negligible in size. This conclusion was robust to a wide array of statistical model specifications. Pragmatically important bias may be present in other aspects of the granting process, but our evidence suggests that it is not present in the initial round of R01 reviews.

Many granting agencies allow reviewers to know the identity of a proposal's principal investigator (PI), which opens the possibility that reviewers discriminate on the basis of PI race and gender. We investigated this experimentally with 48 NIH R01 grant proposals, representing a broad range of NIH-funded science. We modified PI names to create separate white male, white female, black male and black female versions of each proposal, and 412 scientists each submitted initial reviews for 3 proposals. We find little to no race or gender bias in initial R01 evaluations, and additionally find that any bias that might have been present must be negligible in size. This conclusion was robust to a wide array of statistical model specifications. Pragmatically, important bias may be present in other aspects of the granting process, but our evidence suggests that it is not present in the initial round of R01 reviews.

Research on reducing or controlling implicit bias has been characterized by a tension between the two goals of reducing lingering intergroup disparities and gaining insight into human cognition. The tension between these two goals has created two distinct research traditions, each of which is characterized by different research questions, methods, and ultimate goals. We argue that the divisions between these research traditions are more apparent than real and that the two research traditions could be synergistic. We attempt to integrate the two traditions by arguing that implicit bias, and the disparities it is presumed to cause, is a public health problem. On the basis of this perspective, we identify shortcomings in our current knowledge of controlling implicit bias and provide a set of recommendations for future research. Keywords: prejudice; stereotyping; intervention; reduction; implicit bias; self-regulation

Research on reducing or controlling implicit bias has been characterized by a tension between the two goals of reducing lingering intergroup disparities and gaining insight into human cognition. The tension between these two goals has created two distinct research traditions, each of which is characterized by different research questions, methods, and ultimate goals. We argue that the divisions between these research traditions are more apparent than real and that the two research traditions could be synergistic. We attempt to integrate the two traditions by arguing that implicit bias, and the disparities it is presumed to cause, is a public health problem. Based on this perspective, we identify shortcomings in our current knowledge of controlling implicit bias and provide a set of recommendations for future research.

The 2016 U.S. presidential election coincided with the rise of the “alternative right,” or alt-right. Alt-right associates have wielded considerable influence on the current administration and on social discourse, but the movement’s loose organizational structure has led to disparate portrayals of its members’ psychology and made it difficult to decipher its aims and reach. To systematically explore the alt-right’s psychology, we recruited two U.S. samples: An exploratory sample through Amazon’s Mechanical Turk ( N = 827, alt-right n = 447) and a larger, nationally representative sample through the National Opinion Research Center’s Amerispeak panel ( N = 1,283, alt-right n = 71–160, depending on the definition). We estimate that 6% of the U.S. population and 10% of Trump voters identify as alt-right. Alt-right adherents reported a psychological profile more reflective of the desire for group-based dominance than economic anxiety. Although both the alt-right and non-alt-right Trump voters differed substantially from non-alt-right, non-Trump voters, the alt-right and Trump voters were quite similar, differing mainly in the alt-right’s especially high enthusiasm for Trump, suspicion of mainstream media, trust in alternative media, and desire for collective action on behalf of Whites. We argue for renewed consideration of overt forms of bias in contemporary intergroup research.

Scholars and activists alike have expressed concern that a form of have expressed alarm over ongoing disparities in legal outcomes between social groups. Based on evidence that measures of implicit bias are correlated with some discriminatory behaviors, many of these scholars and activists have concluded that implicit bias causes these disparities. We argue that studies of the correlation between implicit measures and behavior are cannot speak strongly to cause. The studies that can speak more strongly to cause suggest that experimentally-induced changes in implicit bias are ephemeral and do not generalize to behavior. We argue that knowledge-based interventions are more likely than implicit bias interventions to fruitfully address legal disparities and illustrate this point with an example, the prejudice habit-breaking intervention.

Contemporary prejudice research focuses primarily on people who are motivated to respond without prejudice and the ways in which unintentional bias can cause these people to act inconsistent with this motivation. However, some real-world phenomena (e.g., hate speech, hate crimes) and experimental findings (e.g., Plant & Devine, 2001; 2009) suggest that some expressions of prejudice are intentional. These phenomena and findings are difficult to explain solely from the motivations to respond without prejudice. We argue that some people are motivated to express prejudice, and we develop the motivation to express prejudice (MP) scale to measure this motivation. In seven studies involving more than 6,000 participants, we demonstrate that, across scale versions targeted at Black people and gay men, the MP scale has good reliability and convergent, discriminant, and predictive validity. In normative climates that prohibit prejudice, the internal and external motivations to express prejudice are functionally non-independent, but they become more independent when normative climates permit more prejudice toward a target group. People high in the motivation to express prejudice are relatively likely to resist pressure to support programs promoting intergroup contact and vote for political candidates who support oppressive policies. The motivation to express prejudice predicted these outcomes even when controlling for attitudes and the motivations to respond without prejudice. This work encourages contemporary prejudice researchers to broaden the range of samples, target groups, and phenomena that they study, and more generally to consider the intentional aspects of negative intergroup behavior.

Despite sincere commitment to egalitarian, meritocratic principles, subtle gender bias persists, constraining women's opportunities for academic advancement. The authors implemented a pair-matched, single-blind, cluster randomized, controlled study of a gender-bias-habit-changing intervention at a large public university.Participants were faculty in 92 departments or divisions at the University of Wisconsin-Madison. Between September 2010 and March 2012, experimental departments were offered a gender-bias-habit-changing intervention as a 2.5-hour workshop. Surveys measured gender bias awareness; motivation, self-efficacy, and outcome expectations to reduce bias; and gender equity action. A timed word categorization task measured implicit gender/leadership bias. Faculty completed a work-life survey before and after all experimental departments received the intervention. Control departments were offered workshops after data were collected.Linear mixed-effects models showed significantly greater changes post intervention for faculty in experimental versus control departments on several outcome measures, including self-efficacy to engage in gender-equity-promoting behaviors (P = .013). When ≥ 25% of a department's faculty attended the workshop (26 of 46 departments), significant increases in self-reported action to promote gender equity occurred at three months (P = .007). Post intervention, faculty in experimental departments expressed greater perceptions of fit (P = .024), valuing of their research (P = .019), and comfort in raising personal and professional conflicts (P = .025).An intervention that facilitates intentional behavioral change can help faculty break the gender bias habit and change department climate in ways that should support the career advancement of women in academic medicine, science, and engineering.

We developed a multi-faceted prejudice habit-breaking intervention to produce long-term reductions in implicit race bias. The intervention is based on the premise that implicit bias is like a habit that can be reduced through a combination of awareness of implicit bias, concern about the effects of that bias, and the application of strategies to reduce bias. In a 12-week longitudinal study, people who received the intervention showed dramatic reductions in implicit race bias. People who were concerned about discrimination or who reported using the strategies showed the greatest reductions. The intervention also led to increases in concern about discrimination and personal awareness of bias over the duration of the study. People in the control group showed none of the above effects. Our results raise the hope of reducing persistent and unintentional forms of discrimination that arise from implicit bias.